{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:10:25Z","timestamp":1760148625097,"version":"build-2065373602"},"reference-count":47,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2023,5,18]],"date-time":"2023-05-18T00:00:00Z","timestamp":1684368000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Fundamental Research Funds for the Central Universities, Sun Yat-sen University","award":["22lgqb09","22qntd0301"],"award-info":[{"award-number":["22lgqb09","22qntd0301"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The increased number of satellites and stations leads to the serious time consumption of the integrated precise orbit determination (POD), especially in the current global navigation satellite system (GNSS) with more than 120 satellites. To improve the computational efficiency of multi-GNSS-integrated POD, this paper proposed an improved parameter estimation method based on intel oneAPI high-performance computing, where the inactive parameters are eliminated in a batch mode. Compared with the classical estimation method based on the \u201cone-by-one\u201d elimination, the efficiencies were significantly improved with ratios of 2.53, 4.21, and 5.38 for 79, 126, and 171 stations\u2019 GPS\/BDS\/Galileo\/GLONASS-integrated POD, respectively. The elapsed time of the improved method by using 126 stations was the same as that of 79 stations\u2019 POD by the classical estimation method. In terms of precision, the one-dimensional root mean square error (RMS) reductions were 0.1 cm (7%), 34.3 cm (11%), 1.9 cm (18%), 0.4 cm (8%), 0.2 cm (13%), and 0.4 cm (13%) for GPS, BDS GEO, BDS IGSO, BDS MEO, Galileo, and GLONASS satellites, respectively.<\/jats:p>","DOI":"10.3390\/rs15102635","type":"journal-article","created":{"date-parts":[[2023,5,18]],"date-time":"2023-05-18T10:17:26Z","timestamp":1684405046000},"page":"2635","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["An Improved Parameter Estimation Method for High-Efficiency Multi-GNSS-Integrated Orbit Determination"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1801-6460","authenticated-orcid":false,"given":"Xingyuan","family":"Yan","sequence":"first","affiliation":[{"name":"School of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai 519082, China"},{"name":"Key Laboratory of Natural Resources Monitoring in Tropical and Subtropical Area of South China, Ministry of Natural Resources, Guangzhou 510300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chenchen","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Shenzhen Polytechnic, Shenzhen 518055, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Meng","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai 519082, China"},{"name":"Key Laboratory of Natural Resources Monitoring in Tropical and Subtropical Area of South China, Ministry of Natural Resources, Guangzhou 510300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Feng","sequence":"additional","affiliation":[{"name":"School of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai 519082, China"},{"name":"Key Laboratory of Natural Resources Monitoring in Tropical and Subtropical Area of South China, Ministry of Natural Resources, Guangzhou 510300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Min","family":"Zhong","sequence":"additional","affiliation":[{"name":"School of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai 519082, China"},{"name":"Key Laboratory of Natural Resources Monitoring in Tropical and Subtropical Area of South China, Ministry of Natural Resources, Guangzhou 510300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5005","DOI":"10.1029\/96JB03860","article-title":"Precise Point Positioning for the Efficient and Robust Analysis of GPS Data from Large Networks","volume":"102","author":"Zumberge","year":"1997","journal-title":"J. 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